Tokenization transforms raw text into searchable tokens through a multi-stage pipeline. The process includes character filtering (lowercasing, removing diacritics), tokenization (splitting text into units using whitespace, n-grams, or structured approaches), stopword removal (filtering common words like 'the' and 'and'), and
Table of contents
Filtering Text With Case and Character FoldingSplitting Text Into Searchable Pieces with TokenizationThrowing Out Filler With StopwordsCutting Down to the Root with StemmingThe Final TokensWhy Tokenization MattersFootnotesSort: